Image edge detection is an integral component of image processing to enhance the clarity of edges and the type of edges. Issues regarding edge techniques were introduced in my 2008 paper on Transforms, Filters and Edge Detectors. The current paper provides a deeper analysis regarding image edge detection using matrices; partial derivatives; convolutions; and the software MATLAB 7.9.0 and the MATLAB Image Processing Toolbox 6.4. Edge detection has applications in all areas of research, including medical research For example, a patient can be diagnosed with an aneurysm by studying the shape of the edges in an angiogram. An angiogram is the visual view of the blood vessels (see Figure The previous paper 15 studied selected letters using vertical, horizontal, and Sobel transforms. This paper will study images to include the letter O and two images, Cameraman and Rice that are included in the Image Processing Toolbox 6.4. We then compare the techniques implemented in the previous paper 15 and the images, letter O and those of Cameraman and Rice, using vertical, horizontal, Sobel, and Canny transforms implementing the software MATLAB 7.9.0 and the Image Processing Toolbox 6.4. Figure 1. Angiogram image of an aortic aneurysm.
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John Schmeelk (2020) studied this question.